ABSTRACT
Cause-effect representations form the foundations for representing systems causality in a number of AI systems. Such a representation can be used for a number of different tasks. It can be used for simulating the behavior of a device, providing explanations about the operation of a device, generating diagnostic knowledge, etc. In this paper, a taxonomy of models of cause-effect relationships of device operation and how these models were used to generate diagnostic knowledge are presented.
